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Scientists in the Computational Life Science (CLS) group at Bayer CropScience in Monhein, Germany, recently joined experts from inside and outside the company for a two-day conference aimed at determining how new DNA sequences could be harnessed to improv | Courtesy of Bayer CropScience

Scientists in the Computational Life Science (CLS) group at Bayer CropScience in Monhein, Germany, recently joined experts from inside and outside the company for a two-day conference aimed at determining how new DNA sequences could be harnessed to improve the health of humans, animals and plants.

Bayer CropScience Head of Research and Development Adrian Percy said the company views the CLS group as one major element to create inter-disciplinary cross-links.

“The 85 researchers in CLS hope to obtain new findings on subjects such as the development of resistances and starting points for new, safe, active ingredients or for the development of new plant traits,” Percy said.

Yves Van de Peer, of Ghent University/VIB in Belgium, said that when large quantities of data are analyzed with computer-based and mathematical models, entirely new findings can be generated and correlations identified.

Barend Mons, of Leiden University in the Netherlands, regards the status of analysis options as critical.

“We are currently missing out on about 95 percent of what would be possible,” Mons said. ”Much information is not available because it is not machine-readable, links are no longer current and databases can´t communicate with each other. In today's world, data is just as important as oil -- but the transport pipelines and options for preparing the new raw material are still largely missing.”

The approximately 100 conference participants unanimously agreed on the pivotal importance of the new opportunities. The two existing pillars on which science is based -- formation of a hypothesis and its subsequent testing through an experiment -- have now been joined by a third pillar, Computational Life Science, or "e-science." This third pillar is necessary in order to cope with the more complex theories, larger quantities of data and teams whose work frequently spans numerous countries.